County level socioeconomic position, work organization and depression disorder: A repeated measures cross-classified multilevel analysis of low-income nursing home workers
Introduction
Over the past two decades, the number of workers holding low-wage jobs as a proportion of the total US workforce has risen. Low-wage work includes jobs that do not enable a full-time worker to support a family of four above the official poverty line (amounting to 17,050 US Dollars; Federal Register, 2000)—or jobs for which workers are paid no more than $8.20 per hour in 2000 dollars (US Department of Health and Human Services and Office of the Secretary, 2000). While not all low-wage workers are primary wage earners, it has been found that one in three low-wage workers in low-income families earn all or most of the family income (Lerman and Skidmore 1999). The low-wage workforce is characterized as tending to be non-unionized (94 percent), disproportionately female (59 percent), white (63 percent), and non-college-educated (62 percent), though recent labor market trends such as educational upgrading and the long-term decline of wages among non-college graduates means that other subpopulations are also increasingly more likely to hold low-wage jobs (Bernstein and Hartmann 1999).
Working conditions are an important determinant of employee physical and psychological well-being. Research has found that low-wage workers, who often do rotating shift work and whose work conditions are often dangerous, hazardous, and even humiliating, are at greater risk for injuries and for poor physical and mental health outcomes (Personick 1990; Myers et al. 2002; Hamermesh, 1999; Brown and Moran 1997; Dooley et al., 2000). In the United States, 70 percent of all low-wage workers are employed in just 10 industries (LEHD, 2001), with low-wage work increasingly concentrated in retail trade (38 percent) and services (39 percent) (Andersson et al., 2003). Today, one of the fastest growing and perhaps most hazardous industries for low-wage workers in the US is the health services industry, in which nearly 60 percent of workers hold low-wage jobs (Kim, 2000). Within the health services industry, the homecare and long-term care divisions are experiencing the most rapid growth in demand for low-wage workers—particularly for personal aides and nurse assistants. In nursing homes, nurse assistants make up the bulk of direct-care support staff and this workforce is expected to increase more than 25 percent by 2006 (Stone and Wiener, 2001). Recently, the US Department of Labor acknowledged not only that this segment of the labor force is generally low-paid, but that frequent violations of federal wage and hour rules occur in nursing home and long-term care work settings (US Department of Labor, 1997). Nursing assistants are thus an appropriate focus for social science research that explores the health effects of low-wage work.
An increased risk of injury among nurse assistants (Personick, 1990) and the physical hazards of nursing home work (Myers et al., 2002) are well established, yet little research has been done to explore the mental health hazards for direct-care nursing home workers (Wunderlich et al., 1996). Nurse assistants employed in nursing homes and other long-term care settings provide direct care for elderly and disabled persons who tend to be very old, cognitively impaired, and functionally dependent in several activities of daily living, such as bathing, feeding, dressing, toileting, and even basic mobility. Many nursing home residents also lack social support networks and thus may further depend on direct-care givers for their social interaction needs. Providing direct care to such a dependent population and establishing emotional attachments to persons who may be either quite ill or near death creates an emotionally demanding work environment for nursing assistants, an environment that is likely to have significant implications for the mental health of these workers (Foner, 1995).
Psychiatric symptoms have been found to figure prominently among the hazards of work organization (Kohn and Schooler, 1973; Karasek, 1979). Mental disorders in the workplace, particularly depression, have important consequences for quality of life, worker productivity, and the utilization and costs of health care (Keita and Sauter, 1992; Sauter et al., 1990). Several studies have found depression to be related to work organization (Karasek, 1979; Mausner-Dorsch and Eaton, 2000; Muntaner et al., 1998; Stansfeld et al., 1998; Grosch and Murphy, 1998). There is also longitudinal evidence linking job demands, lack of autonomy, and monotony at work to affective disorders (Stansfeld et al., 1999; Eaton et al., 2001). More recently, some multilevel studies have found workplace and organizational level characteristics to be related to poor mental health (Söderfeldt et al., 1997; De Jonge et al., 1999; Yperen and Snijders, 2005; Elovainio et al., 2000), while others have begun to provide evidence supporting the link between county level variables and poor mental health outcomes (Jia et al. 2004). For studies exploring the health effects of low-wage work, county level variables are also of theoretical significance because, as Bureau of Labor Statistics data indicate, strong geographic patterns exist in the distribution of low-wage employment, suggesting that important structural economic and social forces are at play in determining the industry-mix of low-wage counties. Furthermore, the organization of health services, including mental health, home care, and long-term care services, is largely organized at the county level and a number of relevant policy interventions such as labor force retraining and living wage ordinances are coordinated at the county level. To date, however, no studies have simultaneously considered the effect of both workplace and county level variables on the mental health outcomes of low-wage workers.
This study uses multilevel analysis to simultaneously test the effect of county, organizational, workplace, and individual level variables on depressive disorders among nursing assistants employed in US nursing homes. More specifically, we test the hypotheses that the individual level variable of age, workplace emotional demands, organizational level variables such as type of nursing home ownership type and seniority wage benefit, and county level indicators of poverty are all associated with depressive disorder among nurse assistants.
Section snippets
Sample and setting
The data used in this study come from two waves of data collection across three US states—a cross-sectional survey done in 2000 and a follow-up survey done in 2002. The cross-sectional data were collected between winter 1999 and spring 2001 from 868 nursing assistants working in 55 nursing homes covered by a single union in three states: West Virginia, Ohio, and Kentucky. Nursing home site-specific lists were obtained from local bargaining unit representatives and all nursing assistants
Results
Descriptive statistics on selected variables for all followed 241 nursing assistants are presented in Table 1. These subjects are mostly women, less than 45 years of age, high school educated, white non-Hispanic, with household incomes less than 200 percent of the poverty line, who work in for-profit nursing homes that do not provide seniority wage increases. Approximately half of these subjects are married, self-report good health, but present symptoms of major depressive disorder.
Table 2
Discussion
The aim of this study was to simultaneously test the effects of county, organizational, workplace, and individual level variables on poor mental health outcomes among low-wage workers in an important US industry. We found that age was not associated with depressive disorder among nursing assistants employed in US nursing homes. Emotional strain, related to providing direct care to elderly and disabled clients, was associated with depressive disorder, as was nursing home ownership type
Acknowledgments
Supported by NIOSH Grant RO1 Award OH03528. Thanks to J. Geiben-Brown for her contribution to the preliminary analysis of this study.
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